[101] | 1 | ;+ |
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[125] | 2 | ; @file_comments |
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| 3 | ; extrapolate data (zinput) where maskinput eq 0 by filling |
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[118] | 4 | ; step by step the coastline points with the mean value of the 8 neighbourgs. |
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[101] | 5 | ; |
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[118] | 6 | ; @param zinput {in}{required} |
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| 7 | ; data to be extrapolate |
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| 8 | ; |
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| 9 | ; @param maskinput {in}{required} |
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| 10 | ; |
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| 11 | ; @param nb_iteration {in}{optional} |
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| 12 | ; number of iteration |
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| 13 | ; |
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| 14 | ; @keyword x_periodic |
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| 15 | ; @keyword MINVAL |
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| 16 | ; @keyword MAXVAL |
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| 17 | ; |
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| 18 | ; @version $Id$ |
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| 19 | ; |
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[101] | 20 | ;- |
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[59] | 21 | FUNCTION extrapolate, zinput, maskinput, nb_iteration, x_periodic = x_periodic, MINVAL = minval, MAXVAL = maxval |
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| 22 | ; |
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[125] | 23 | compile_opt idl2, strictarrsubs |
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[59] | 24 | ; |
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| 25 | ; check the number of iteration used in the extrapolation. |
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| 26 | IF n_elements(nb_iteration) EQ 0 THEN nb_iteration = 10.E20 |
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| 27 | IF nb_iteration EQ 0 THEN return, zinput |
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| 28 | nx = (size(zinput))[1] |
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| 29 | ny = (size(zinput))[2] |
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| 30 | ; take care of the boundary conditions... |
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[125] | 31 | ; |
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[59] | 32 | ; for the x direction, we put 2 additional columns at the left and |
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[125] | 33 | ; right side of the array. |
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[59] | 34 | ; for the y direction, we put 2 additional lines at the bottom and |
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[125] | 35 | ; top side of the array. |
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[59] | 36 | ; These changes allow us to use shift function without taking care of |
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| 37 | ; the x and y periodicity. |
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| 38 | ; |
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| 39 | ztmp = bytarr(nx+2, ny+2) |
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| 40 | ztmp[1:nx, 1:ny] = byte(maskinput) |
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| 41 | msk = temporary(ztmp) |
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| 42 | ; |
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| 43 | ztmp = replicate(1.e20, nx+2, ny+2) |
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| 44 | ztmp[1:nx, 1:ny] = zinput |
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| 45 | if keyword_set(x_periodic) then begin |
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| 46 | ztmp[0, 1:ny] = zinput[nx-1, *] |
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| 47 | ztmp[nx+1, 1:ny] = zinput[0, *] |
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| 48 | ENDIF |
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| 49 | ; remove NaN points if there is some... |
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| 50 | nan = where(finite(ztmp) EQ 0, cnt_nan) |
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| 51 | IF cnt_nan NE 0 THEN ztmp[temporary(nan)] = 1.e20 |
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| 52 | z = temporary(ztmp) |
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| 53 | nx2 = nx+2 |
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| 54 | ny2 = ny+2 |
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| 55 | ;--------------------------------------------------------------- |
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| 56 | ;--------------------------------------------------------------- |
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[125] | 57 | ; extrapolation |
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[59] | 58 | ;--------------------------------------------------------------- |
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| 59 | sqrtinv = 1./sqrt(2) |
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| 60 | ; |
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[69] | 61 | cnt = 1 |
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[125] | 62 | ; When we look for the coast line, we don't want to select the |
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[59] | 63 | ; borderlines of the array. -> we force the value of the mask for |
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| 64 | ; those lines. |
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| 65 | msk[0, *] = 1b |
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| 66 | msk[nx+1, *] = 1b |
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| 67 | msk[*, 0] = 1b |
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| 68 | msk[*, ny+1] = 1b |
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| 69 | ; find the land points |
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| 70 | land = where(msk EQ 0, cnt_land) |
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| 71 | ;--------------------------------------------------------------- |
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| 72 | WHILE cnt LE nb_iteration AND cnt_land NE 0 DO BEGIN |
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| 73 | ;--------------------------------------------------------------- |
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| 74 | ; find the coast line points... |
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| 75 | ;--------------------------------------------------------------- |
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| 76 | ; Once the land points list has been found, we change back the the |
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| 77 | ; mask values for the boundary conditions. |
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| 78 | msk[0, *] = 0b |
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| 79 | msk[nx+1, *] = 0b |
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| 80 | msk[*, 0] = 0b |
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| 81 | msk[*, ny+1] = 0b |
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| 82 | if keyword_set(x_periodic) then begin |
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| 83 | msk[0, *] = msk[nx, *] |
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| 84 | msk[nx+1, *] = msk[1, *] |
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| 85 | endif |
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| 86 | ; |
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| 87 | ; we compute the weighted number of sea neighbourgs. |
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| 88 | ; those 4 neighbours have a weight of 1: |
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[125] | 89 | ; * |
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| 90 | ; *+* |
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| 91 | ; * |
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[59] | 92 | ; |
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| 93 | ; those 4 neighbours have a weight of 1/sqrt(2): |
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| 94 | ; |
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| 95 | ; * * |
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[125] | 96 | ; + |
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[59] | 97 | ; * * |
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| 98 | ; |
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| 99 | ; As we make sure that none of the land points are located on the |
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| 100 | ; border of the array, we can compute the weight without shift |
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| 101 | ; (faster). |
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| 102 | ; |
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| 103 | weight = msk[land+1]+msk[land-1]+msk[land+nx2]+msk[land-nx2] $ |
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| 104 | +sqrtinv*(msk[land+nx2+1]+msk[land+nx2-1] $ |
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| 105 | +msk[land-nx2+1]+msk[land-nx2-1]) |
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| 106 | ; list all the points that have sea neighbourgs |
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| 107 | ok = where(weight GT 0) |
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| 108 | ; the coastline points |
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| 109 | coast = land[ok] |
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| 110 | ; their weighted number of sea neighbourgs. |
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| 111 | weight = weight[temporary(ok)] |
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| 112 | ;--------------------------------------------------------------- |
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| 113 | ; fill the coastine points |
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| 114 | ;--------------------------------------------------------------- |
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| 115 | z = temporary(z)*msk |
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| 116 | ; |
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| 117 | zcoast = z[1+coast]+z[-1+coast]+z[nx2+coast]+z[-nx2+coast] $ |
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| 118 | +1./sqrt(2)*(z[nx2+1+coast]+z[nx2-1+coast] $ |
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| 119 | +z[-nx2+1+coast]+z[-nx2-1+coast]) |
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[125] | 120 | ; |
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[59] | 121 | IF n_elements(minval) NE 0 THEN zcoast = minval > temporary(zcoast) |
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| 122 | IF n_elements(maxval) NE 0 THEN zcoast = temporary(zcoast) < maxval |
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| 123 | z[coast] = temporary(zcoast)/temporary(weight) |
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| 124 | ; we update the the boundary conditions of z |
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| 125 | if keyword_set(x_periodic) then begin |
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| 126 | z[0, *] = z[nx, *] |
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| 127 | z[nx+1, *] = z[1, *] |
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| 128 | endif |
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| 129 | ;--------------------------------------------------------------- |
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| 130 | ; we update the mask |
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| 131 | ;--------------------------------------------------------------- |
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| 132 | msk[temporary(coast)] = 1 |
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| 133 | ; |
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| 134 | cnt = cnt + 1 |
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[125] | 135 | ; When we look for the coast line, we don't want to select the |
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[59] | 136 | ; borderlines of the array. -> we force the value of the mask for |
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| 137 | ; those lines. |
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| 138 | msk[0, *] = 1b |
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| 139 | msk[nx+1, *] = 1b |
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| 140 | msk[*, 0] = 1b |
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| 141 | msk[*, ny+1] = 1b |
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| 142 | ; find the land points |
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| 143 | land = where(msk EQ 0, cnt_land) |
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| 144 | ; |
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| 145 | ENDWHILE |
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| 146 | ;--------------------------------------------------------------- |
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| 147 | ; we return the original size of the array |
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| 148 | ;--------------------------------------------------------------- |
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[125] | 149 | ; |
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[59] | 150 | return, z[1:nx, 1:ny] |
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[125] | 151 | END |
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[59] | 152 | |
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